1. Field of the Invention
The present invention relates to impedance pneumography and more particularly is directed toward suppressing cardiovascular artifact within a respiration signal obtained through impedance pneumography.
2. Description of the Prior Art
A respiration signal is a measure of a patient's transthoracic impedance, that is, the impedance across a patient's chest which varies primarily due to the expansion and contraction of the lungs during breathing. Heart and blood motion also cause a change in the chest size, and thus, a change in the respiration signal. Thus, the respiration signal really comprises both a breath component and a component due to heart and blood motion referred to hereinafter as to cardiovascular artifact.
Therefore, in determining a condition of apnea in the patient, that is, whether the patient has ceased breathing it is highly desirable to identify and suppress those components in the respiration signal which are due to heart and blood motion so that the time duration between breaths can be measured. Otherwise, cardiovascular artifacts can be mistakenly interpreted as breath events when, in fact, a condition of apnea exists. On the other hand, if the breath component of the respiration signal is suppressed in order to remove cardiovascular artifacts, the filtered respiration signal may be incorrectly interpreted as representing a condition of apnea.
One general solution for suppressing cardiovascular artifacts from the respiration signal is based on the fact that cardiovascular artifacts normally have frequencies near or above the heart rate. Accordingly, as long as the heart rate is greater than the breath rate, the cardiovascular artifact within the respiration signal can be greatly reduced, that is, suppressed by removing those components of the respiration signal having frequencies at or above the heart rate. The resulting filtered respiration signal will contain basically only the breath component. The removal, that is, the filtering of such selected frequencies based on another time variant parameter such as heart rate is commonly referred to as adaptive filtering.
Prior art adaptive filters for suppressing cardiovascular artifacts from a respiration signal, commonly referred to as cardiovascular artifact (CVA) filters, typically implement a scheme in which a signal sample is added to previous samples which have been multiplied by one of a number of different coefficients. The choice of coefficients which vary in value based on the heart rate determines the filter's characteristics.
In today's computer era, CVA filtering schemes are typically implemented by employing one or more microprocessors. These microprocessors besides processing the CVA filtering scheme are used for undertaking a number of other tasks which are unrelated to the filtering scheme. In light of these other tasks, the processing time required to execute the above adaptive filtering scheme has taken on added importance. In this regard, the above CVA filtering scheme is considered less than optimal since the frequent change of coefficients requires a relatively large amount of execution time. Additionally such an adaptive filtering scheme requires an undesirable amount of hardware, that is, memory for storing these coefficients. The additional execution time and memory required, of course, result in a more expensive microprocessor system.